The combination of Shewhart control charts and an exponentially weighted moving average (EWMA) control charts to simultaneously monitor shifts in the mean output of a production process has proven very effective in handling both small and large shifts. To improve the sensitivity of the control chart to detect off-target processes, we propose a combined Shewhart-EWMA (CSEWMA) control chart for m...

Automated public health records provide the necessary data for rapid outbreak detection. An adaptive exponentially weighted moving average EWMA plan is developed for signalling unusually high incidence when monitoring a time series of nonhomogeneous daily disease counts. A Poisson transitional regression model is used to fit background/expected trend in counts and provides “one-day-ahead” forec...

The control chart is an important statistical technique that is used to monitor the quality of a process. Shewhart control charts are used to detect larger disturbances in the process parameters, whereas CUSUM and EWMA charts are meant for smaller and moderate changes. Runs rules schemes are generally used to enhance the performance of Shewhart control charts. In this study, we propose two runs...

A detailed comparison is made of volatility forecasting techniques on Australian value-weighted indices. The techniques compared are the naı̈ve approach (historical volatility), an improved extreme-value method (IEV), the ARCH/GARCH class of models and an exponentially weighted moving average (EWMA) of volatility. The study suggests that the EWMA technique appears to be the best volatility forec...

Recently, various types of technology funds became available to support the programs for technology development and commercialization of SMEs (Small and Medium Enterprise) in Korea. However, the potential financial performances have not been sufficiently considered at the selection stage of fund recipient SMEs whereas the default risk has been a major concern. This paper proposes a CBR (Case Ba...

The double EWMA (exponentially weighted moving average) control method is a popular algorithm for adjusting a process from run to run in semiconductor manufacturing. Until recently, the dEWMA controller had been applied only for the single controllable factor (or input), single quality charcteristic (or output) case. Recently, Del Castillo and Rajagopal [4] propose a multivariate double EWMA co...

This paper considers the problem of combining multiple models to achieve a prediction accuracy not much worse than that of the best single model for least squares regression. It is known that if the models are mis-specified, model averaging is superior to model selection. Specifically, let n be the sample size, then the worst case regret of the former decays at the rate of O(1/n) while the wors...

We examine how to forecast after a recent break. We consider monitoring for change and then combining forecasts from models that do and do not use data before the change; and robust methods, namely rolling regressions, forecast averaging over different windows and exponentially weighted moving average (EWMA) forecasting. We derive analytical results for the performance of the robust methods rel...

Nonparametric (distribution-free) control charts have been introduced in recent years when quality characteristics do not follow a specific distribution. When the sample selection is prohibitively expensive, we prefer ranked-set sampling over simple random because ranked set sampling-based outperform charts. In this study, proposed nonparametric homogeneously weighted moving average based on Wi...